The evolution of the Circular Economy - mapping research and practice

Funded through a competitively won PhD Scholarship from AMBS, this mixed-methods project combines quantitative machine learning methods with qualitative social science methods to map the evolution of the concept of circular economy.

This concept is currently surging among practitioners as the dominant label of addressing issues of resource efficiency and recycling. These topics have been the topic of attention of academics and practitioners for decades, but in the last five years, the circular economy label has become a key focus. The project maps this evolution and seeks to explain it. In addition, the project will produce case studies of the adoption of the label in cities, to better understand the actual application of the label in networks of firms, policymakers and civil society organizations.

Team:

Sampriti Mahanty (PhD Student, AMBS)

Frank Boons (1st supervisor)

Riza Batista Navarro (2nd supervisor)

Julia Handl (2nd supervisor)

Outputs:

Jiao, W. & Boons, F. (2017) Policy durability of Circular Economy in China: A process analysis of policy translation, Resources, Conservation and Recycling, 117, 12-24.

Jiao, W., Boons, F., Teisman, G. & Li, C. (2018) Durable policy facilitation of Sustainable Industrial Parks in China: A perspective of co-evolution of policy processes, Journal of Cleaner Production, 192, 179-190.

Mahanty, S., Boons, F., Handl, J. & Batista-Navarro, R. (2019) Studying the Evolution of the ‘Circular Economy’ Concept Using Topic Modelling, in Yin, H., Camacho, D., Tino, P., Tallón-Ballesteros, A., Menezes, R. & Allmendinger, R. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2019, Lecture Notes in Computer Science, 11872. Springer, Cham. 

Mahanty, S., Boons, F., Handl, J. & Batista-Navarro, R.T. (2019) Understanding the Evolution of Circular Economy through Language Change, Proceedings of the 1st International Workshop on Computational Approaches to Historical Language Change, 250-253.